Multi-Factorized Semi-covariance of Stock Markets and Gold Price

Jun Huang; Mei Huang; Lin Yang; Yun Shi

doi:10.20944/preprints202103.0224.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 5 March 2021 / Approved: 8 March 2021 / Online: 8 March 2021 (13:44:31 CET)

Complex models have received significant interest in recent years and are being increasingly used to explain the stochastic phenomenon with upward and downward fluctuation such as the stock market. Different from existing semi-variance methods in traditional integer dimension construction for two variables, this paper proposes a simplified multi-factorized fractional dimension derivation with the exact Excel tool algorithm involving the fractional center moment extension to covariance, which is a complex parameter average that is a multi-factorized extension to Pearson covariance. By examining the peaks and troughs of gold price averages, the proposed algorithm provides more insight into revealing underlying stock market trends to see who is the financial market leader during good economic times. The calculation results demonstrate that the complex covariance is able to distinguish subtle differences among stock market performances and gold prices for the same field that the two variable covariance may overlook. We take the London, Tokyo, Shanghai, Toronto and Nasdaq as the representative examples.

Fractional moment; stock exchange; multiple factor; semi variance

MATHEMATICS & COMPUTER SCIENCE, Algebra & Number Theory

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Received: 4 May 2021
Commenter:

Jun Steed Huang

The commenter has declared there is no conflict of interests.

Comment: https://www.mdpi.com/1911-8074/14/4/172

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Multi-Factorized Semi-covariance of Stock Markets and Gold Price

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